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An efficient cellular flow model for cohesive particle flocculation in turbulence

Published online by Cambridge University Press:  24 February 2020

K. Zhao ,
B. Vowinckel Open the ORCID record for B. Vowinckel [Opens in a new window] ,
T.-J. Hsu ,
T. Köllner ,
B. Bai Open the ORCID record for B. Bai [Opens in a new window]  and
E. Meiburg Open the ORCID record for E. Meiburg [Opens in a new window]
K. Zhao
Affiliation:
Department of Mechanical Engineering, UC Santa Barbara, CA 93106, USA State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
B. Vowinckel
Affiliation:
Department of Mechanical Engineering, UC Santa Barbara, CA 93106, USA Leichtweiß-Institut für Wasserbau, Technische Universität Braunschweig, 38106 Braunschweig, Germany
T.-J. Hsu
Affiliation:
Center for Applied Coastal Research, Department of Civil & Environmental Engineering, University of Delaware, Newark, DE 19716, USA
T. Köllner*
Affiliation:
Department of Mechanical Engineering, UC Santa Barbara, CA 93106, USA
B. Bai
Affiliation:
State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
E. Meiburg*
Affiliation:
Department of Mechanical Engineering, UC Santa Barbara, CA 93106, USA
*
‡Present address: CADFEM GmbH, 85567 Grafing, Germany
†Email address for correspondence: [email protected]
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Abstract

We propose a one-way coupled model that tracks individual primary particles in a conceptually simple cellular flow set-up to predict flocculation in turbulence. This computationally efficient model accounts for Stokes drag, lubrication, cohesive and direct contact forces on the primary spherical particles, and allows for a systematic simulation campaign that yields the transient mean floc size as a function of the governing dimensionless parameters. The simulations reproduce the growth of the cohesive flocs with time, and the emergence of a log-normal equilibrium distribution governed by the balance of aggregation and breakage. Flocculation proceeds most rapidly when the Stokes number of the primary particles is $O(1)$. Results from this simple computational model are consistent with experimental observations, thus allowing us to propose a new analytical flocculation model that yields improved agreement with experimental data, especially during the transient stages.

JFM classification

Geophysical and Geological Flows: Sediment transport Multiphase and Particle-laden Flows: Particle/fluid flow Complex Fluids: Suspensions
Type
JFM Rapids
Information
Journal of Fluid Mechanics , Volume 889 , 25 April 2020 , R3
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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